This paper presents a new method for synthesising chemical process models that combines prior knowledge and fuzzy models. The hybrid convolution model consists of a fuzzy model based steady-state, and an impulse response model based dynamic part. Prior knowledge enters to the dynamic part as a resident time distribution model of the process. The proposed approach is applied in the modelling and model based control of a highly nonlinear pH process.